Pub Date : 2025-12-17DOI: 10.1016/j.jlp.2025.105890
Tylee L. Kareck , Chi-Yang Li , Jiejia Wang , Michael J. Gollner , Qingsheng Wang
Modern data centers are becoming increasingly vital infrastructure, yet several recent high-profile fire incidents have exposed persistent vulnerabilities. As artificial intelligence (AI) technologies continue to advance, these risks will only intensify. Contributing causes of such fires include electrical faults, battery failures, cooling system malfunctions, and human error. This perspective paper synthesizes key information from recently reported incidents and discusses practical fire safety strategies for both prevention (i.e., AI-driven fault detection and fire-safe battery storage) and suppression (i.e., clean agents and liquid nitrogen system). Emerging technologies are highlighted as potential fire safety enhancements, and their development and implementation in modern data centers are recommended. Two relevant methods for fire risk assessment are explored, specifically non-scenario-based consideration of common fire causes and scenario-based examination of recent incidents. These assessment methods should be utilized while considering engineering design practices, operational feasibility, and regulatory alignment to enhance resilience and promote adoption in modern data centers. This work intends to offer a perspective on data center fire risk assessment by examining past incidents, presenting insights into current knowledge gaps, and proposing future research and stakeholder efforts for the improvement of data center fire safety.
{"title":"From incident to insight: Fire risk in modern data centers","authors":"Tylee L. Kareck , Chi-Yang Li , Jiejia Wang , Michael J. Gollner , Qingsheng Wang","doi":"10.1016/j.jlp.2025.105890","DOIUrl":"10.1016/j.jlp.2025.105890","url":null,"abstract":"<div><div>Modern data centers are becoming increasingly vital infrastructure, yet several recent high-profile fire incidents have exposed persistent vulnerabilities. As artificial intelligence (AI) technologies continue to advance, these risks will only intensify. Contributing causes of such fires include electrical faults, battery failures, cooling system malfunctions, and human error. This perspective paper synthesizes key information from recently reported incidents and discusses practical fire safety strategies for both prevention (i.e., AI-driven fault detection and fire-safe battery storage) and suppression (i.e., clean agents and liquid nitrogen system). Emerging technologies are highlighted as potential fire safety enhancements, and their development and implementation in modern data centers are recommended. Two relevant methods for fire risk assessment are explored, specifically non-scenario-based consideration of common fire causes and scenario-based examination of recent incidents. These assessment methods should be utilized while considering engineering design practices, operational feasibility, and regulatory alignment to enhance resilience and promote adoption in modern data centers. This work intends to offer a perspective on data center fire risk assessment by examining past incidents, presenting insights into current knowledge gaps, and proposing future research and stakeholder efforts for the improvement of data center fire safety.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105890"},"PeriodicalIF":4.2,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study employs laser schlieren imaging and pressure measurement techniques to investigate the impact of kaolin (Ko) on the explosion behavior of CH4/H2 mixtures at various equivalence ratios (0.8, 1.0 and 1.2) and H2 contents (0, 0.3 and 0.9). Results indicate that the inhibitory effect of Ko first increases and then decreases with increasing concentration, achieving optimal suppression at 175 g/m3. Under the same equivalent ratios (φ), the reduction in maximum explosion pressure (Pmax) becomes more pronounced with higher H2 addition (R). At constant R but varying φ, the suppression effect exhibits a different trend: when R = 0 and 0.3, optimal suppression occurs at φ = 0.8. Whereas at R = 0.9, the optimal suppression effect is observed at φ = 1.0, corresponding to a 30.27 % reduction in Pmax. As the Ko concentration increases, dust enhances flow field instability, thereby accelerating the transformation of the flame structure. Meanwhile, higher hydrogen addition (R) intensifies chemiluminescence, and heated Ko particles to emit strong intense thermal radiation. The combined effect of these two factors causes the flame to appear bright white-yellow. A coupled analysis of flame propagation and pressure evolution reveals that, despite differences in φ, the coupled evolution of flame and pressure remains highly similar under the same R. The main distinctions arise in the timing of critical flame development stage and flame brightness. Overall, Ko suppresses explosions primarily through physical mechanisms such as endothermic cooling, dilution and isolation effects, and thermal radiation shielding, and it exhibits particularly strong suppression at high H2 additions.
{"title":"Inhibitory effects of varying kaolin concentrations on CH4/H2 explosion characteristics","authors":"Shanshan Liu, Dongxu Huang, Yong Pan, Zhenhua Wang, Juncheng Jiang","doi":"10.1016/j.jlp.2025.105889","DOIUrl":"10.1016/j.jlp.2025.105889","url":null,"abstract":"<div><div>This study employs laser schlieren imaging and pressure measurement techniques to investigate the impact of kaolin (Ko) on the explosion behavior of CH<sub>4</sub>/H<sub>2</sub> mixtures at various equivalence ratios (0.8, 1.0 and 1.2) and H<sub>2</sub> contents (0, 0.3 and 0.9). Results indicate that the inhibitory effect of Ko first increases and then decreases with increasing concentration, achieving optimal suppression at 175 g/m<sup>3</sup>. Under the same equivalent ratios (<em>φ</em>), the reduction in maximum explosion pressure (<em>P</em><sub>max</sub>) becomes more pronounced with higher H<sub>2</sub> addition (<em>R</em>). At constant <em>R</em> but varying <em>φ</em>, the suppression effect exhibits a different trend: when <em>R</em> = 0 and 0.3, optimal suppression occurs at <em>φ</em> = 0.8. Whereas at <em>R</em> = 0.9, the optimal suppression effect is observed at <em>φ</em> = 1.0, corresponding to a 30.27 % reduction in <em>P</em><sub>max</sub>. As the Ko concentration increases, dust enhances flow field instability, thereby accelerating the transformation of the flame structure. Meanwhile, higher hydrogen addition (<em>R</em>) intensifies chemiluminescence, and heated Ko particles to emit strong intense thermal radiation. The combined effect of these two factors causes the flame to appear bright white-yellow. A coupled analysis of flame propagation and pressure evolution reveals that, despite differences in <em>φ</em>, the coupled evolution of flame and pressure remains highly similar under the same <em>R</em>. The main distinctions arise in the timing of critical flame development stage and flame brightness. Overall, Ko suppresses explosions primarily through physical mechanisms such as endothermic cooling, dilution and isolation effects, and thermal radiation shielding, and it exhibits particularly strong suppression at high H<sub>2</sub> additions.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105889"},"PeriodicalIF":4.2,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-16DOI: 10.1016/j.jlp.2025.105888
Jiayue Wang , Huanyu Wang , Liangchang Shen , Liping Kou , Yunhe Tong
In the process industries, incident investigations repeatedly show that deficiencies in evacuation guidance systems contribute to casualties during fires, explosions, and toxic releases. Effective guidance that performs reliably under such hazardous conditions is therefore a critical component of process safety and loss prevention. However, traditional evacuation drills often lack realism, repeatability, and inclusivity, limiting their value for hazard mitigation and safety system optimisation. This study develops a Virtual Reality (VR)-based evacuation simulation platform designed for both safety training and empirical evaluation of evacuation guidance strategies. The system models a five-story enclosed building with configurable layouts, emergency broadcasts, and multiple signage types (graphic-only, text-based, combined, and enhanced with directional or supplementary cues). It enables safe, repeatable testing of human response to process-related emergency scenarios, recording detailed behavioural metrics such as movement trajectories, decision points, and evacuation time. In the case study, 88 % of participants deviated from the designated route at least once, and several intersections showed 10–30 misjudgements. Misjudgement frequency strongly predicted evacuation time, and the optimal signage–broadcast configurations substantially reduced average evacuation times for both hearing-impaired and cognitively impaired participants. The results revealed frequent navigation errors and highlighted guidance combinations tailored to different user needs, such as prominent door and wall signage for hearing-impaired individuals and early verbal alerts aligned with visual cues for those with cognitive impairments. This work introduces a practical tool for loss prevention in the process industries, supporting the design and verification of evacuation systems, training programs, and architectural layouts in alignment with process safety objectives.
{"title":"Design and implementation of a VR-based evacuation simulation system: A case study with impaired people","authors":"Jiayue Wang , Huanyu Wang , Liangchang Shen , Liping Kou , Yunhe Tong","doi":"10.1016/j.jlp.2025.105888","DOIUrl":"10.1016/j.jlp.2025.105888","url":null,"abstract":"<div><div>In the process industries, incident investigations repeatedly show that deficiencies in evacuation guidance systems contribute to casualties during fires, explosions, and toxic releases. Effective guidance that performs reliably under such hazardous conditions is therefore a critical component of process safety and loss prevention. However, traditional evacuation drills often lack realism, repeatability, and inclusivity, limiting their value for hazard mitigation and safety system optimisation. This study develops a Virtual Reality (VR)-based evacuation simulation platform designed for both safety training and empirical evaluation of evacuation guidance strategies. The system models a five-story enclosed building with configurable layouts, emergency broadcasts, and multiple signage types (graphic-only, text-based, combined, and enhanced with directional or supplementary cues). It enables safe, repeatable testing of human response to process-related emergency scenarios, recording detailed behavioural metrics such as movement trajectories, decision points, and evacuation time. In the case study, 88 % of participants deviated from the designated route at least once, and several intersections showed 10–30 misjudgements. Misjudgement frequency strongly predicted evacuation time, and the optimal signage–broadcast configurations substantially reduced average evacuation times for both hearing-impaired and cognitively impaired participants. The results revealed frequent navigation errors and highlighted guidance combinations tailored to different user needs, such as prominent door and wall signage for hearing-impaired individuals and early verbal alerts aligned with visual cues for those with cognitive impairments. This work introduces a practical tool for loss prevention in the process industries, supporting the design and verification of evacuation systems, training programs, and architectural layouts in alignment with process safety objectives.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105888"},"PeriodicalIF":4.2,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.jlp.2025.105887
Lingfeng Wang , Haiyan Chen , Zhengdong Liu , Chang Li , Chunmiao Yuan
<div><div>Coal dust explosions pose a major threat to the safety of industrial processes involving coal handling and utilization (e.g., coal mining, coal processing, and coal-fired power generation). The Minimum Ignition Temperature (MIT), as a core parameter for evaluating the risk of coal dust explosions in industrial process safety management, is influenced by multiple coupled factors including water immersion time, coalification degree, volatile matter content, and particle size distribution. This study systematically investigates the mechanism by which coal dust characteristics affect the MIT in the context of industrial water-related coal handling processes and builds a multi-factor predictive model using experimental testing and machine learning methods—with the goal of providing a tool for process safety risk mitigation. The Godbert-Greenwald furnace was employed to measure the MIT of coal dust clouds under various water immersion conditions. Key influencing factors were identified through Pearson and Spearman correlation analyses, with a focus on their relevance to process parameter optimization. The XG-Boost algorithm was utilized to develop a predictive model with features such as water immersion time, volatile matter content, active functional group content, median particle size, dust cloud concentration, and wettability. The results indicate that the volatile matter content (Pearson coefficient −0.78, <em>p</em> < 0.001) and active functional group content (Spearman coefficient −0.71, <em>p</em> < 0.001) are strongly negatively correlated with MIT, serving as key determinants influencing MIT in coal-related industrial processes. Water immersion time shows a moderate negative correlation with MIT (Spearman coefficient −0.50, <em>p</em> < 0.001), with prolonged immersion reducing MIT by 60°C—this elucidates how moisture (a controllable process factor) changes the hydroxyl content and pore structure of coal dust surfaces, thereby lowering the activation energy of oxidation and increasing process safety risks. The XG-Boost model ranks feature importance as follows: volatile matter content > active functional group content > water immersion time > wettability > dust cloud concentration > median particle size—providing clear guidance for prioritizing process parameter monitoring. The determination coefficients (<em>R</em><sup><em>2</em></sup>) for the model training and testing datasets are 0.9999 and 0.9512, with average absolute errors (<em>MAE</em>) of 1.470 × 10<sup>−4</sup> and 1.647, demonstrating a high level of predictive accuracy for supporting real-time process safety decision-making. This study offers a theoretical foundation for the dynamic assessment of coal dust explosion risks in industrial processes with variable coal quality and controllable process parameters. It is advised that in industrial process safety practice, emphasis should be placed on monitoring volatile matter and active functional grou
{"title":"Model and mechanism of the impact of water immersion process on the minimum ignition temperature of coal dust","authors":"Lingfeng Wang , Haiyan Chen , Zhengdong Liu , Chang Li , Chunmiao Yuan","doi":"10.1016/j.jlp.2025.105887","DOIUrl":"10.1016/j.jlp.2025.105887","url":null,"abstract":"<div><div>Coal dust explosions pose a major threat to the safety of industrial processes involving coal handling and utilization (e.g., coal mining, coal processing, and coal-fired power generation). The Minimum Ignition Temperature (MIT), as a core parameter for evaluating the risk of coal dust explosions in industrial process safety management, is influenced by multiple coupled factors including water immersion time, coalification degree, volatile matter content, and particle size distribution. This study systematically investigates the mechanism by which coal dust characteristics affect the MIT in the context of industrial water-related coal handling processes and builds a multi-factor predictive model using experimental testing and machine learning methods—with the goal of providing a tool for process safety risk mitigation. The Godbert-Greenwald furnace was employed to measure the MIT of coal dust clouds under various water immersion conditions. Key influencing factors were identified through Pearson and Spearman correlation analyses, with a focus on their relevance to process parameter optimization. The XG-Boost algorithm was utilized to develop a predictive model with features such as water immersion time, volatile matter content, active functional group content, median particle size, dust cloud concentration, and wettability. The results indicate that the volatile matter content (Pearson coefficient −0.78, <em>p</em> < 0.001) and active functional group content (Spearman coefficient −0.71, <em>p</em> < 0.001) are strongly negatively correlated with MIT, serving as key determinants influencing MIT in coal-related industrial processes. Water immersion time shows a moderate negative correlation with MIT (Spearman coefficient −0.50, <em>p</em> < 0.001), with prolonged immersion reducing MIT by 60°C—this elucidates how moisture (a controllable process factor) changes the hydroxyl content and pore structure of coal dust surfaces, thereby lowering the activation energy of oxidation and increasing process safety risks. The XG-Boost model ranks feature importance as follows: volatile matter content > active functional group content > water immersion time > wettability > dust cloud concentration > median particle size—providing clear guidance for prioritizing process parameter monitoring. The determination coefficients (<em>R</em><sup><em>2</em></sup>) for the model training and testing datasets are 0.9999 and 0.9512, with average absolute errors (<em>MAE</em>) of 1.470 × 10<sup>−4</sup> and 1.647, demonstrating a high level of predictive accuracy for supporting real-time process safety decision-making. This study offers a theoretical foundation for the dynamic assessment of coal dust explosion risks in industrial processes with variable coal quality and controllable process parameters. It is advised that in industrial process safety practice, emphasis should be placed on monitoring volatile matter and active functional grou","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105887"},"PeriodicalIF":4.2,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-13DOI: 10.1016/j.jlp.2025.105883
Xin-Yue Ma , Yan Tang , Fang-Chao Cao , Jun-Cheng Jiang , An-Chi Huang
This study examines the combined suppression of n-heptane pool fires using modified expandable graphite (EGML) and additive-enhanced water mist (WM-APG-ML). EGML, formulated with MgCl2·6H2O and inert additives, generates denser carbon layers during expansion, whereas WM-APG-ML demonstrates diminished surface tension (26.82 mN/m) and smaller droplet size, enhancing flame penetration. Fire suppression trials conducted in a 1.5 m3 chamber revealed that the integrated system extinguished flames within 12 s, utilizing merely 68 g of EGML and 2.5 L of water mist. In comparison to the control group (ABC powder and NaCl water mist), this indicates a 59% decrease in the usage of extinguishing agents. The findings demonstrate that the combination of physical isolation, rapid cooling, and free radical quenching markedly enhances fire-extinguishing efficacy and diminishes the danger of re-ignition, offering a novel approach for oil fire suppression.
{"title":"Synergistic fire suppression of n-heptane pool flames using modified expandable graphite and additive-enhanced water mist","authors":"Xin-Yue Ma , Yan Tang , Fang-Chao Cao , Jun-Cheng Jiang , An-Chi Huang","doi":"10.1016/j.jlp.2025.105883","DOIUrl":"10.1016/j.jlp.2025.105883","url":null,"abstract":"<div><div>This study examines the combined suppression of n-heptane pool fires using modified expandable graphite (EGML) and additive-enhanced water mist (WM-APG-ML). EGML, formulated with MgCl<sub>2</sub>·6H<sub>2</sub>O and inert additives, generates denser carbon layers during expansion, whereas WM-APG-ML demonstrates diminished surface tension (26.82 mN/m) and smaller droplet size, enhancing flame penetration. Fire suppression trials conducted in a 1.5 m<sup>3</sup> chamber revealed that the integrated system extinguished flames within 12 s, utilizing merely 68 g of EGML and 2.5 L of water mist. In comparison to the control group (ABC powder and NaCl water mist), this indicates a 59% decrease in the usage of extinguishing agents. The findings demonstrate that the combination of physical isolation, rapid cooling, and free radical quenching markedly enhances fire-extinguishing efficacy and diminishes the danger of re-ignition, offering a novel approach for oil fire suppression.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105883"},"PeriodicalIF":4.2,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-13DOI: 10.1016/j.jlp.2025.105882
Junjie Gu , Xinglin Wen , Yong Pan , Lei Ni
1-methyl-2,4-cyclohexanediamine (2,4-MCHD) is the core raw material for the synthesis of high-grade polyurethane. Aiming at the problems of long reaction time and safety risks in batch reactors, a fast and safe synthesis scheme of 2,4-MCHD was proposed. The one-pot catalytic hydrogenation of 2, 4-dinitrotoluene (2, 4-DNT) to 2, 4-MCHD was investigated in a microfilled bed reactor (μPBR) over the 5 %LiOH-5 %Ru/γ-Al2O3 catalyst. The effects of temperature, pressure, gas and liquid volumetric were investigated. Under the optimized condition (180 °C, 7 MPa H2 pressure, 0.6 mL/min liquid flow rate, 40 mL/min gas flow rate), within a residence time of 144 s, the conversion of 2,4-DNT and the selectivity of 2,4-MCHD exceeded 99 % and 80 %, respectively. Compared to the conventional batch mode, an increase of one to two orders of magnitude in space-time-yield (STY) was realized under continuous flow mode. Furthermore, the inherent risks of high-pressure hydrogenation in batch processes are significantly mitigated in the μPBR due to its minimal hydrogen inventory and superior heat and mass transfer characteristics.
{"title":"Fast and continuous synthesis of 1-methyl-2,4-cyclohexanediamine in a micro-packed bed reactor","authors":"Junjie Gu , Xinglin Wen , Yong Pan , Lei Ni","doi":"10.1016/j.jlp.2025.105882","DOIUrl":"10.1016/j.jlp.2025.105882","url":null,"abstract":"<div><div>1-methyl-2,4-cyclohexanediamine (2,4-MCHD) is the core raw material for the synthesis of high-grade polyurethane. Aiming at the problems of long reaction time and safety risks in batch reactors, a fast and safe synthesis scheme of 2,4-MCHD was proposed. <strong>The one-pot catalytic hydrogenation of 2, 4-dinitrotoluene (2, 4-DNT) to 2, 4-MCHD was investigated in a microfilled bed reactor (μPBR)</strong> over the 5 %LiOH-5 %Ru/γ-Al<sub>2</sub>O<sub>3</sub> catalyst. The effects of temperature, pressure, gas and liquid volumetric were investigated. Under the optimized condition (180 °C, 7 MPa H<sub>2</sub> pressure, 0.6 mL/min liquid flow rate, 40 mL/min gas flow rate), within a residence time of 144 s, the conversion of 2,4-DNT and the selectivity of 2,4-MCHD exceeded 99 % and 80 %, respectively. Compared to the conventional batch mode, an increase of one to two orders of magnitude in space-time-yield (STY) was realized under continuous flow mode. Furthermore, the inherent risks of high-pressure hydrogenation in batch processes are significantly mitigated in the μPBR due to its minimal hydrogen inventory and superior heat and mass transfer characteristics.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105882"},"PeriodicalIF":4.2,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-13DOI: 10.1016/j.jlp.2025.105884
Huaying Cui , Jinlong Zhao , Dina Zhang , Xin Kong , Jianping Zhang
Confined space operation involves working in (semi-)enclosed spaces. While confined space is an important workspace in chemical industry and urban development, there is also an increased risk of injury or even death due to hazardous factors, such as limited entry and exit area or a lack of adequate ventilation. In this paper, an intelligent method was proposed combining knowledge graph (KG), association rules mining (ARM) and Bayesian network (BN) to assess the risk and determine the key factors for confined space operation. First, a causative indicator system was established using 601 previous accidents, for which KG was also constructed to allow automatic extraction of accident causes. Based on the association rules determined by ARM, a risk assessment method was developed using BN. The key factors were analyzed and countermeasures were proposed. The results show that the association between failure to conduct ventilation detection on the site and failure to wear safety protective equipment demonstrates significant correlation strength, while association rule between inadequate safety education and training and failure to wear safety protective equipment also high. By the analysis in BN, it can be seen that the probability of confined space operation accidents is significantly higher (59 %) with the baseline probability of nodes in BN. The other important factors include failure to wear safety protective equipment, blindly rescue, insufficient provision of protective equipment and operation without a license. This study can evaluate the risk and determine key factors in a data-driven manner to reduce the subjectivity, which provides a reference for the targeted safety management of confined space operation.
{"title":"Risk assessment and key factors analysis of confined space operation using knowledge graph, association rules mining and Bayesian network","authors":"Huaying Cui , Jinlong Zhao , Dina Zhang , Xin Kong , Jianping Zhang","doi":"10.1016/j.jlp.2025.105884","DOIUrl":"10.1016/j.jlp.2025.105884","url":null,"abstract":"<div><div>Confined space operation involves working in (semi-)enclosed spaces. While confined space is an important workspace in chemical industry and urban development, there is also an increased risk of injury or even death due to hazardous factors, such as limited entry and exit area or a lack of adequate ventilation. In this paper, an intelligent method was proposed combining knowledge graph (KG), association rules mining (ARM) and Bayesian network (BN) to assess the risk and determine the key factors for confined space operation. First, a causative indicator system was established using 601 previous accidents, for which KG was also constructed to allow automatic extraction of accident causes. Based on the association rules determined by ARM, a risk assessment method was developed using BN. The key factors were analyzed and countermeasures were proposed. The results show that the association between failure to conduct ventilation detection on the site and failure to wear safety protective equipment demonstrates significant correlation strength, while association rule between inadequate safety education and training and failure to wear safety protective equipment also high. By the analysis in BN, it can be seen that the probability of confined space operation accidents is significantly higher (59 %) with the baseline probability of nodes in BN. The other important factors include failure to wear safety protective equipment, blindly rescue, insufficient provision of protective equipment and operation without a license. This study can evaluate the risk and determine key factors in a data-driven manner to reduce the subjectivity, which provides a reference for the targeted safety management of confined space operation.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105884"},"PeriodicalIF":4.2,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1016/j.jlp.2025.105880
Qifen Wu , Minggao Yu
This study investigates the explosion characteristics of nonuniform methane–air mixtures under lateral vent conditions, focusing on the interplay between vent positions, pressure dynamics, and flame propagation behaviors. Experiments were conducted in a vertical duct with varying lateral vent configurations, employing uniform and stratified methane–air mixtures. The findings reveal that lateral venting has dual effects of suppression and promotion on explosion intensity. Although vent openings mitigate internal energy and combustible gas accumulation, external explosions triggered by pressure differentials generate backflow that accelerate flame propagation. Specifically, the A1 lateral vent configuration dissipates pressure waves near the vent, minimizing the impact of methane heterogeneity on peak pressures. By contrast, the A2 configuration exhibits overlapping pressure oscillation curves between the uniform and nonuniform mixtures during early stages, with distinct resonance phase divergences in peak timing and magnitude. Top venting demonstrates significantly weaker pressure oscillations compared to lateral setups. Flame propagation transitions from unidirectional upward motion to oscillatory patterns upon vent interaction, with mid-duct lateral vents inducing flame–pressure wave resonance to maximize pressure values. The differences between top and lateral venting stem from directional mismatches: lateral vents facilitate initial flame discharge via lower regions, forming dual-vortex external flames, and top vents maintain columnar downstream propagation. These findings clarify the influence of vent positioning on explosion dynamics and recommend that top vents or bottom near-end side vents be prioritized over mid-duct vents in industrial ducts handling non-uniform methane-air mixtures.
{"title":"Characterization of nonuniform methane–air mixture explosions under lateral vent conditions","authors":"Qifen Wu , Minggao Yu","doi":"10.1016/j.jlp.2025.105880","DOIUrl":"10.1016/j.jlp.2025.105880","url":null,"abstract":"<div><div>This study investigates the explosion characteristics of nonuniform methane–air mixtures under lateral vent conditions, focusing on the interplay between vent positions, pressure dynamics, and flame propagation behaviors. Experiments were conducted in a vertical duct with varying lateral vent configurations, employing uniform and stratified methane–air mixtures. The findings reveal that lateral venting has dual effects of suppression and promotion on explosion intensity. Although vent openings mitigate internal energy and combustible gas accumulation, external explosions triggered by pressure differentials generate backflow that accelerate flame propagation. Specifically, the A1 lateral vent configuration dissipates pressure waves near the vent, minimizing the impact of methane heterogeneity on peak pressures. By contrast, the A2 configuration exhibits overlapping pressure oscillation curves between the uniform and nonuniform mixtures during early stages, with distinct resonance phase divergences in peak timing and magnitude. Top venting demonstrates significantly weaker pressure oscillations compared to lateral setups. Flame propagation transitions from unidirectional upward motion to oscillatory patterns upon vent interaction, with mid-duct lateral vents inducing flame–pressure wave resonance to maximize pressure values. The differences between top and lateral venting stem from directional mismatches: lateral vents facilitate initial flame discharge via lower regions, forming dual-vortex external flames, and top vents maintain columnar downstream propagation. These findings clarify the influence of vent positioning on explosion dynamics and recommend that top vents or bottom near-end side vents be prioritized over mid-duct vents in industrial ducts handling non-uniform methane-air mixtures.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105880"},"PeriodicalIF":4.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The reactivity hazards of aromatic nitro compounds remain one of the most serious concern in the chemical industry in spite of continual research and attention devoted to them. The exothermic onset temperature (To) is one of the most important thermal stability parameters for risk assessment and safe management of aromatic nitro compounds. The quantitative structure–property relationship (QSPR) between the exothermic onset temperature and molecular structure of aromatic nitro compounds was investigated. 63 aromatic nitro compounds were collected. The simplex representation of molecular structure (SiRMS) descriptors was calculated. The six SiRMS descriptors were screened out by the genetic algorithm–multivariable linear regression (GA-MLR) method as input variables to establish an MLR model and two nonlinear models, support vector machines (SVM) and random forest (RF). The performance and parameters of the models were examined, and Williams plots were used to determine the range of applicability domain of the models. The results showed that the performance of the nonlinear model was better than that of the linear model, and the RF model performed the best. Compared with the existing models, the three developed models have significantly improved in model fitting ability, stability, and predictive ability. This paper provides a new method for predicting To of aromatic nitro compounds for engineering.
{"title":"Prediction of the exothermic onset temperature of aromatic nitro compounds by the SiRMS descriptors from molecular structures","authors":"Yinyan Zhang , Xin Zhang , Shengjie Niu , Yong Pan","doi":"10.1016/j.jlp.2025.105876","DOIUrl":"10.1016/j.jlp.2025.105876","url":null,"abstract":"<div><div>The reactivity hazards of aromatic nitro compounds remain one of the most serious concern in the chemical industry in spite of continual research and attention devoted to them. The exothermic onset temperature (To) is one of the most important thermal stability parameters for risk assessment and safe management of aromatic nitro compounds. The quantitative structure–property relationship (QSPR) between the exothermic onset temperature and molecular structure of aromatic nitro compounds was investigated. 63 aromatic nitro compounds were collected. The simplex representation of molecular structure (SiRMS) descriptors was calculated. The six SiRMS descriptors were screened out by the genetic algorithm–multivariable linear regression (GA-MLR) method as input variables to establish an MLR model and two nonlinear models, support vector machines (SVM) and random forest (RF). The performance and parameters of the models were examined, and Williams plots were used to determine the range of applicability domain of the models. The results showed that the performance of the nonlinear model was better than that of the linear model, and the RF model performed the best. Compared with the existing models, the three developed models have significantly improved in model fitting ability, stability, and predictive ability. This paper provides a new method for predicting To of aromatic nitro compounds for engineering.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105876"},"PeriodicalIF":4.2,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.jlp.2025.105879
Yan Li , Lingyuan Lan , Tianshuo Zhang , Yiqing Jia , Yixiao Zhang , Yu Shan , Yan Li , Kun Zhang , Jun Xie
Lithium-ion batteries serve as the core energy storage units in modern battery energy storage systems (BESS). However, their susceptibility to thermal runaway poses significant risks of fire and explosion, making safety a critical concern. To address this challenge, smoke detectors are commonly employed in BESS containers for early warning, which need to be connected via cables/lines for power and signal transmission. Nevertheless, the current arrangement of smoke detection systems predominantly relies on semi-quantitative experience and regulations, lacking a scientifically rational design methodology. This may lead to a smoke detection system with unsatisfied detection sensitivity or unnecessary wires. To overcome this limitation, an optimized layout design approach for smoke detection systems based on the black-winged kite algorithm (BKA) is proposed, aiming to minimize wiring length while fulfilling system response time requirements. First, a simulation model of the BESS container is established using fire dynamics simulator (FDS), and the smoke detector's obscuration rate over time is obtained. Second, an optimization model is constructed to achieve the technical and economic targets, which is reducing the wire length while guaranteeing the detection system's sensitivity. The BKA is utilized to derive the optimal smoke detector arrangement. Finally, the robustness of the detection system is evaluated based on the cumulative failure probability of detectors. Case studies demonstrate that, compared to traditional optimization algorithms, the BKA exhibits significant advantages in convergence speed and accuracy. The proposed method ensures that the system can reliably trigger an alarm within 10 s during a thermal runaway fire in any battery cabinet with the minimum number of detectors. The robustness analysis results confirm that even under detector failure conditions, the system can still maintain reliable alarm performance within 10 s. The proposed smoke detector layout design approach reduces installation costs by 33.39 % compared to an additional redundant detector. This study provides theoretical support and practical references for the scientific design of fire detection systems in BESS containers.
{"title":"Optimized smoke detector layout design approach for battery energy storage system containers based on black-winged kite algorithm","authors":"Yan Li , Lingyuan Lan , Tianshuo Zhang , Yiqing Jia , Yixiao Zhang , Yu Shan , Yan Li , Kun Zhang , Jun Xie","doi":"10.1016/j.jlp.2025.105879","DOIUrl":"10.1016/j.jlp.2025.105879","url":null,"abstract":"<div><div>Lithium-ion batteries serve as the core energy storage units in modern battery energy storage systems (BESS). However, their susceptibility to thermal runaway poses significant risks of fire and explosion, making safety a critical concern. To address this challenge, smoke detectors are commonly employed in BESS containers for early warning, which need to be connected via cables/lines for power and signal transmission. Nevertheless, the current arrangement of smoke detection systems predominantly relies on semi-quantitative experience and regulations, lacking a scientifically rational design methodology. This may lead to a smoke detection system with unsatisfied detection sensitivity or unnecessary wires. To overcome this limitation, an optimized layout design approach for smoke detection systems based on the black-winged kite algorithm (BKA) is proposed, aiming to minimize wiring length while fulfilling system response time requirements. First, a simulation model of the BESS container is established using fire dynamics simulator (FDS), and the smoke detector's obscuration rate over time is obtained. Second, an optimization model is constructed to achieve the technical and economic targets, which is reducing the wire length while guaranteeing the detection system's sensitivity. The BKA is utilized to derive the optimal smoke detector arrangement. Finally, the robustness of the detection system is evaluated based on the cumulative failure probability of detectors. Case studies demonstrate that, compared to traditional optimization algorithms, the BKA exhibits significant advantages in convergence speed and accuracy. The proposed method ensures that the system can reliably trigger an alarm within 10 s during a thermal runaway fire in any battery cabinet with the minimum number of detectors. The robustness analysis results confirm that even under detector failure conditions, the system can still maintain reliable alarm performance within 10 s. The proposed smoke detector layout design approach reduces installation costs by 33.39 % compared to an additional redundant detector. This study provides theoretical support and practical references for the scientific design of fire detection systems in BESS containers.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105879"},"PeriodicalIF":4.2,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}